This invention relates to digital communication systems, including but not limited to radio frequency (RF) digital communication systems.
Digital communication systems often employ forward error correction coding techniques in which input signals are encoded prior to modulation and transmission over a communications channel (e.g., an RF channel) by adding redundant bits that can be used for the detection and correction of errors. At the receiver, the signal is demodulated and decoded, yielding received sequences of bits (xe2x80x9creceived signalsxe2x80x9d) that may differ from the input signal due to the effects of various channel impairments such as, for example, noise, fading or interference. Various coding/decoding methods have been developed for the purpose of detecting and correcting errors in the received signals.
Hard decoding methods employ slicing the received samples into a predetermined set of quantized values (e.g., xe2x80x9c0xe2x80x9d or xe2x80x9c1xe2x80x9d in a binary system). Forward error correction is performed on the recovered quantized values using methods such as, for example, Golay, Reed-Solomon, or Hamming codes, as are well known in the art. Hard decision codes use a parity matrix to recover each transmitted symbol, thereby allowing for counting the errors found in the received signal yielding a bit error count or bit error rate which may be used to judge the quality of the communication channel. The ability to judge channel quality with a quantifiable value such as a bit error count is useful for a variety of reasons, as will be appreciated by those skilled in the art. For example, where signal(s) are received from multiple sites, bit error counts allow for determining the best of the multiple received signals. Generally, however, hard decision codes, notwithstanding their advantages, are less effective in terms of error correction capability than soft decision codes.
Soft decision codes operate upon received blocks of data derived from a convolutional encoder (e.g., by time-shifting input bits through a shift register). The xe2x80x9cstatexe2x80x9d of an encoder at any given time is characterized by the rightmost Kxe2x88x921 bits in the shift register, where K is the number of stages of the shift register. For example, in a convolutional encoder with a 3-stage shift register, the possible states are the rightmost two bits of the encoder (e.g., 00, 10, 01 or 11). The possible states and transitions between states of a convolutional encoder may be represented by a trellis diagram. Soft decision decoding is usually implemented with a Viterbi or trellis type decoder which, in essence, works backwards through the trellis to determine the most likely input signal, as is known in the art.
Generally, soft decision decoding allows for better performance than hard-decision decoding but there is no way for soft decision decoders to determine an exact bit error count or bit error rate to quantify the success of the decoding algorithm. It is known that a quality value for soft decision decoders may be derived from a minimum path metric associated with the Viterbi algorithm. However, such quality value is based on summing the noise difference between a number of received signals and the most likely input signal and is subject to fairly wide variations depending on the precision of the digital processor being used. For example, in ASTRO(trademark) digital data systems, available from Motorola, Inc., the value derived from the minimum path metric is dependent on the unsliced symbol values and their corresponding signal strength, each of which is affected by the front end processing performed in the receiver. Thus, the value derived from the minimum path metric can range from 1 to 2xe2x88x9223 in the ASTRO(trademark) systems. Quality values having such a wide variations are of limited utility in comparing signal(s) received from multiple sites unless the value can be xe2x80x9cnormalizedxe2x80x9d (e.g, compressed or scaled) between sites. However, normalization is difficult, at best, where the quality value is so dependent on properties of receivers because those properties can vary, over time, or can change as the receivers are replaced or maintained in the field.
Accordingly, there is a need for determining a quantifiable value for measuring the quality of trellis decoded block data, which value is independent of variations between receivers and may be used in communication systems to compare the quality of signals received from multiple sites. The present invention is directed to satisfying or at least partially satisfying this need.